Adaptive divergence in resistance to herbivores in Datura stramonium

Introduction

Most species consist of a series of populations that are often phenotypically differentiated (Rice & Jain, 1985; Thompson, 2005). Heritable phenotypic differentiation in multiple traits can be effectively produced by processes like genetic drift, mutation, founder effects or population isolation (Gomulkiewicz et al., 2007). However, phenotypic differentiation in traits that contribute to individuals’ fitness may also have a spatial structure caused by varying selective regimes exerted by biotic and/or abiotic factors (Holsinger & Weir, 2009). Furthermore, stabilizing selection may promote phenotypic similarity among populations (Merilä & Crnokrak, 2001). Elucidating to what extent these processes promote character differentiation among populations is central if we are to fully understand the prevalence of among-population variation in the wild (Lynch, 1990; Althoff & Thompson, 1999; Criscione, Blouin & Sunnucks, 2006; Kelly, 2006; Gomulkiewicz et al., 2007). Here we aimed to determine if among-population variation in traits that confer resistance to herbivores in the annual plant Datura stramonium is consistent with a scenario of varying selection or genetic drift and restricted gene flow.

To infer whether natural selection explains the observed differentiation among populations in putatively adaptive quantitative characters (Q_ST), it is necessary to contrast this hypothesis against a null model of differentiation at adaptively neutral loci (F_ST; Spitze, 1993; Martin, Chapuis & Goudet, 2008; Whitlock, 2008). The detection of a significant difference between the estimators of differentiation, Q_ST and F_ST, may imply adaptive differentiation among populations. The comparison of the differentiation indices has three possible outcomes each with a unique interpretation (see Table 1 in Merilä & Crnokrak, 2001). When Q_ST and F_ST are statistically equal, this implies that the degree of differentiation in quantitative traits could be produced by drift alone. This does not necessarily imply that genetic drift produced the observed phenotypic differentiation but that the roles of selection and drift are indiscernible. When Q_ST < F_ST, it means that natural selection might be favoring the same phenotype across populations. Finally, when Q_ST significantly exceeds F_ST, it means that directional selection is favoring different phenotypes in different populations. When Q_ST and F_ST are equal, it is expected that both indices, estimated among pairs of populations of the same species, will be positively correlated, implying isolation by distance, restricted gene flow and genetic drift (although a partial role of selection could be involved also), or high recombination between molecular neutral marker loci and quantitative trait loci (Merilä & Crnokrak, 2001). In contrast, no correlation between both indices of differentiation among local populations may implicate a role of natural selection (see ‘Discussion’).

In order to explore the signals of non-neutral evolution in quantitative traits it is necessary to estimate Q_ST and F_ST. F_ST is commonly estimated by analyzing variance in allele frequency (Wright, 1951) at molecular markers, like microsatellite loci. On the other hand, to estimate Q_ST it is necessary to know the amount of additive genetic variance of quantitative traits in many local populations (Spitze, 1993). However, accomplishing the latter objective is not feasible for a large number of populations because it requires estimating the breeding values of genotypes (families) for a suite of phenotypic characters in each local population. P_ST (degree of phenotypic differentiation index) is an analogous index to Q_ST (Leinonen et al., 2006; Leinonen et al., 2013), useful for exploring if phenotypic differentiation among populations exceeds genetic differentiation in neutral markers (Merilä & Crnokrak, 2001). The use of P_ST instead of Q_ST is justified when estimates of additive genetic variance are not available (Leinonen et al., 2006; Leinonen et al., 2013; Lehtonen et al., 2009). Estimation of additive genetic variation in traits makes it necessary to obtain the phenotypic covariance between relatives (families) with an experimental common garden and/or the use of reciprocal transplant experiments to rule out the environmental effects on phenotypes. Hence, P_ST can be used as a surrogate of Q_ST.

Resistance traits exhibited by plants (i.e., traits that prevent/reduce damage by natural enemies) vary widely across populations (Núñez-Farfán, Fornoni & Valverde, 2007; Züst et al., 2012). Selection exerted by herbivores is a major force driving the evolution of plants’ resistance traits (Rausher, 2001; Anderson & Mitchell-Olds, 2011; Züst et al., 2012). Thus, among-population differentiation in resistance traits is likely to be produced by spatial variation in the local selective regimes exerted by herbivores. Such spatially variable selection can be generated by among-population variation in the abundance, species composition, feeding styles, and degree of dietary specialization of herbivores to their host plants (Falconer & Mackay, 1996; Charlesworth, Nordborg & Charlesworth, 1997; Parchman & Benkman, 2002; Arany et al., 2008; Hare, 2012). Datura stramonium (Solanaceae) provides an optimal system for studying among-population differentiation in resistance traits. Because of its wide distribution (Mexico, Canada, United States, and Europe), D. stramonium is exposed to different environmental conditions and to a wide diversity of herbivore species (Weaver & Warwick, 1984; Valverde, Fornoni & Núñez-Farfán, 2001; Cuevas-Arias, Vargas & Rodríguez, 2008). Resistance against herbivores in D. stramonium includes leaf trichomes (Valverde, Fornoni & Núñez-Farfán, 2001; Kariñho-Betancourt & Núñez-Farfán, 2015) and tropane alkaloids (Shonle & Bergelson, 2000), of which atropine, hyosciamine and scopolamine are the most abundant (Parr et al., 1990; Kariñho-Betancourt et al., 2015). These secondary metabolites affect the activity of the neurotransmitter acetylcholine (Roddick, 1991) with negative effects on insects and vertebrate herbivores (Hsiao & Fraenkel, 1968; Krug & Proksch, 1993; Wink, 1993; Shonle, 1999; Mithöfer & Boland, 2012). Recent studies have found ample geographic variation in leaf trichome density and atropine and scopolamine concentration in central Mexico (Castillo et al., 2013; Castillo et al., 2014). However, it is unclear if selection by herbivores or neutral processes, among other factors, can account for the observed among-population differentiation in these resistance traits.

Here, we assessed to what extent population differentiation in resistance leaf traits (trichome density, atropine and scopolamine concentrations) of D. stramonium is accounted by neutral processes (genetic drift and restricted gene flow) or divergent natural selection. To do so, we compared the degree of phenotypic differentiation of resistance traits by means of P_ST estimated for the whole range of values of heritability, with the neutral expectation set by allelic divergence at microsatellite loci (F_ST). We expect that P_ST of each resistance character would be significantly higher than the index of population differentiation in neutral molecular markers (F_ST), since previous studies have detected contrasting selection exerted by herbivores on the three characters.

Methods

Fieldwork

During August–September 2007 we sampled 13 natural populations of D. stramonium in central Mexico (Fig. 1). Selected populations inhabit a wide range of habitat types. The geographic location and habitat characteristics are shown in Table 1. From each population we sampled 30 randomly chosen individual plants.

Table 1:

Vegetation type, latitude, longitude, altitude and population means of leaf trichome density, and atropine and scopolamine concentrations of 13 populations of Datura stramonium in central Mexico.

	Vegetation type	Latitude	Longitude	Altitude (m a.s.l.)	Trichome density (2.5 × mm2)	Atropine (mg/g)	Scopolamine (mg/g)
1. Acatzingo	DS	−97.78	19.32	2,160	8.99	0.295	0.159
2. Atlixco	DS	−98.42	18.98	1,840	9.04	0.691	0.577
3. Esperanza	DS	−97.37	18.85	2,278	9.57	0.535	0.542
4. Patria Nueva	DS	−98.96	20.38	2,040	12.62	0.317	0.367
5. Taxco	TDF	−99.66	18.5	1,582	9.02	0.957	0.266
6. Teotihuacán	DS	−98.86	19.68	2,294	8.73	0.437	0.353
7. Ticumán	TDF	−99.2	18.86	1,210	6.6	0.938	1.889
8. Tlaxiaca	DS	−98.86	20.08	2,340	9.36	0.288	0.458
9. Tula	DS	−99.35	20.05	2,020	6.06	3.129	2.804
10. Tzin Tzun Tzan	POF	−101.58	19.63	2,050	4.29	0.994	2.995
11. Valsequillo	DS	−98.11	18.91	2,209	6.09	1.767	0.044
12. Xalmimilulco	POF	−98.38	19.2	1,200	4.66	2.688	2.513
13. Zirahuén	POF	−101.91	19.43	2,174	4.91	0.618	1.968

DOI: 10.7717/peerj.1411/table-1

Notes:

DS

desert shrub

POF

Pine–Oak forest

TDF

tropical deciduous forest

Results

Among-population variation in resistance traits

A multivariate analysis of variance (MANOVA) detected significant multivariate differences in the studied resistance traits of 13 populations of D. stramonium (Wilks’ λ = 0.091, F_36,331.64 = 11.51, P < 0.0001). After the subsequent univariate ANOVAs were applied, we found significant differences in trichome density (F_12,126 = 5.10, P < 0.0001), atropine (F_12,126 = 7.85, P < 0.0001), and scopolamine concentration (F_12,126 = 23.33, P < 0.0001). Mean leaf trichome density and mean atropine and scopolamine concentration per population are shown in Fig. 2 and Table 1.

Phenotypic divergence in resistance traits

Comparison of phenotypic (P_ST) and neutral genetic marker divergence (F_ST) showed that P_ST values for scopolamine concentration were significantly higher than the F_ST in all values of h² (Fig. 3). However, P_ST for atropine concentration was significantly higher than F_ST when 0 ≥ h² ≤ 0.3 (Fig. 2), whereas P_ST of leaf trichome density significantly exceeded F_ST only when h² ≤ 0.1 (Fig. 2).

Discussion

Results showed that phenotypic differentiation in resistance traits among population of D. stramonium is not consistent with divergence promoted by genetic drift and restricted gene flow alone (Pujol et al., 2008; Lehtonen et al., 2009). Phenotypic differentiation in scopolamine concentration was significantly higher than F_ST across the range of h². In contrast, genetic differentiation in trichome density was different from F_ST only when heritability was very low, and most phenotypic variation could be related to major environmental factors, like annual mean precipitation and temperature. Likewise, differentiation in atropine concentration seems to differ from the neutral expectation only at low values of h². Furthermore, we did not find a correlation between pair-wise neutral genetic distances and phenotypic distances of any of the three resistance traits. Taken together, results suggest that natural selection could be involved in phenotypic divergence on resistance traits among populations of D. stramonium.

Results indicate that populations of D. stramonium are differentiated in both phenotypic and neutral molecular markers. We found a moderate amount of differentiation among populations at microsatellite loci (F_ST = 0.228). Using this F_ST value, the indirect estimate of gene flow (Nm) is 0.846, suggesting restricted gene flow among populations of D. stramonium, and not sufficient to prevent differentiation by genetic drift (Hedrick, 2000). This contrasts with differentiation at neutral loci reported for other organisms where F_ST is generally lower than 0.228 (but see Merilä & Crnokrak, 2001). P_ST index values statistically not different from this value of F_ST imply that quantitative phenotypic characters follow a pattern of drift-induced divergence (Leinonen et al., 2006). Here, we found that the P_ST index of scopolamine was significantly higher than F_ST for all values of heritability considered (cf. Fig. 3). This result strongly suggests that phenotypic differentiation among populations in scopolamine concentration is congruent with a scenario of divergent selection exerted by herbivores among populations. However, P_ST of atropine and leaf trichome density was higher than F_ST only when heritability was ≤0.3 and ≤0.1, respectively. This implies that the proportion of genetic variance among populations from total genetic variance is high for these characters (Lehtonen et al., 2009; Leinonen et al., 2013). When genetic variance within populations is low, as implied by low values of heritability, there is a high opportunity to detect a significant P_ST given that the among-population genetic variance component has a relevant weight in the total phenotypic variance. Inversely, when heritability is high, the within-population genetic component accounts for a high fraction of total genetic variance rendering P_ST very small. These considerations may explain why P_ST of trichome density and atropine are different from F_ST only at very low heritability.

Although P_ST is used as an analog of Q_ST (genetic differentiation in quantitative characters) when it is not possible to obtain the amount of additive genetic variation (variance among families, within populations) (Merilä & Crnokrak, 2001), conclusions derived from these estimations must be interpreted with caution since this index can be biased by all environmental variation due to abiotic conditions among localities as well as environmental deviations within populations, and non-additive genetic variation (v.gr., epistatic interactions, dominance, linkage disequilibrium), among others (Pujol et al., 2008). Thus is relevant to ask whether P_ST index obtained for the resistance traits in D. stramonium posses genetic variance. Datura stramonium displays a great variation among populations in trichome density and tropane alkaloids’ concentration in central Mexico (Castillo et al., 2013). Phenotypic variation in alkaloid concentration, like other quantitative traits, is governed by environmental physical factors and genetic variation (Castillo et al., 2013). Previous studies in this species have detected narrow-sense h² of general resistance to herbivores of 0.49 and 0.41 in two natural populations of D. stramonium (Fornoni, Valverde & Núñez-Farfán, 2003; note that general resistance may include physical and chemical defenses). In addition, broad-sense h² of general resistance and trichome density has been estimated in 0.25 and 0.64, respectively (Kariñho-Betancourt & Núñez-Farfán, 2015). Also, genetic variance in trichome density among-populations (Valverde, Fornoni & Núñez-Farfán, 2001) and general resistance (Valverde, Fornoni & Núñez-Farfán, 2003; Carmona & Fornoni, 2013) has been detected in D. stramonium. Finally, genetic variance in alkaloid concentration (hyosciamine and scopolamine, and their ratio) has been detected previously by Shonle & Bergelson (2000). Thus, there is ample evidence of genetic basis of phenotypic variation in resistance of D. stramonium to support our estimation of P_ST values.

Because a P_ST index higher than F_ST means that divergent selection might be involved in population differentiation of resistance traits, at least for scopolamine, it is relevant to ask to what extent natural selection by herbivores is responsible for population differentiation in this character. In D. stramonium, several lines of evidence strongly suggest that differentiation in resistance is accounted by for herbivores. Differential and contrasting selection gradients on resistance to herbivores were detected between two populations of this species in a reciprocal transplant experiment (Fornoni, Valverde & Núñez-Farfán, 2004). Likewise, Shonle & Bergelson (2000) detected stabilizing selection on hyosciamine and directional selection to reduce scopolamine concentration in D. stramonium. In a recent study of eight populations of D. stramonium, Castillo et al. (2014) found that atropine is selected against by the dietary specialist herbivores Epitrix parvula (in one population) and Lema daturaphila (in two populations). In contrast, scopolamine was positively selected in one population where the specialist Lema daturaphila was the main herbivore, whereas trichome density was positively selected in two populations (one with L. daturaphila and one with the generalist grasshopper Sphenarium puprurascens), and negatively selected in one population with the E. parvula (Castillo et al., 2014). Thus, although genetic drift and restricted gene flow could produce phenotypic variation in plant resistance among populations, the available evidence of spatially variable selection on resistance traits in D. stramonium and data presented here suggests that population differentiation can be potentially adaptive.

Furthermore, we did not detect any significant correlation between the pair-wise P_ST and F_ST among population across the whole range of heritability, suggesting that differentiation at quantitative traits and neutral molecular loci is decoupled. Theoretically, if the pace of differentiation is dictated by genetic drift only, it is expected that differentiation indices will be perfectly and positively correlated (r = 1, P_ST = F_ST; Fig. 4). If the correlation is positive but lower than 1, then genetic drift has a role but does not explain all differentiation in quantitative traits. In the region above the diagonal in Fig. 4, where P_ST > F_ST, any positive pair-wise correlation across populations, depicts a scenario where differentiation in quantitative traits exceeds the neutral expectation and suggests divergent selection (Fig. 4). On the other hand, in the region below the diagonal, where P_ST < F_ST, any positive pair-wise correlation across populations, portrays a scenario where differentiation at neutral molecular loci surpasses that of quantitative characters suggesting a strong effect of genetic drift; however at moderate values of F_ST stabilizing selection might be favoring the same phenotype across populations (Fig. 4). When P_ST > F_ST and are uncorrelated (dotted line in Fig. 4) it shows another interesting scenario, as found here. This implies that genetic drift and restricted gene flow alone cannot explain (Pujol et al., 2008) the pattern of differentiation among populations in resistance traits in D. stramonium. Under this scenario there is opportunity for divergence driven by selection in resistance traits. Our results suggest that the higher P_ST than F_ST for scopolamine, together with spatial variation in resistance traits and the existence of a selection mosaic detected previously by Castillo et al. (2014) are consistent with outcomes predicted by the geographic mosaic of coevolution (Thompson, 2005).

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